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, Physics, Computer Science, or a related field. Hands-on experience with computational materials methods (e.g., DFT, molecular dynamics, machine learning force field simulations). Proficiency in Python
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). • Required Skills: 1. Strong background in statistical mechanics and thermodynamics 2. Proficiency in first-principles calculations (VASP, Quantum Espresso) and molecular dynamics simulations (LAMMPS, OpenMM
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, molecular dynamics, and machine learning, to model battery electrolyte and solid electrolyte interphase (SEI), while collaborating with experimentalists. Qualifications • Ph.D. in Computational Materials
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). Hands-on experience with computational materials methods (e.g., DFT, molecular dynamics, phase-field simulations). Proficiency in Python, TensorFlow/PyTorch, and scientific computing. Experience in
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& design, catalyst design & modelling, and carbon capturing & conversion. Proficiency in fluidized reactor design & optimization, hydrodynamics & molecular dynamics modelling (openFOAM, Ansys Fluent, LAMMPS